Good MLOps Practices & tools for Computer Vision and Batch Scoring Projects

Program

• 18:00 - 19:00 Talk + Discussion
• 19:00 - 20:30 Networking

Talk

This talk discusses the landscape of practices and tools that may be beneficial to your ML projects. We discuss differences on MLOps between Batch Scoring and Computer Vision use cases. This discussion may help you to design MLOps processes for your projects, set priorities and tools to explore.

Also, the talk reviews open-source tools that are worth paying attention to. Of course, the focus is on such tools as DVC (Data Version Control) and CML (Continuous Machine Learning). However, other tools are considered as well.

Should you attend?

• As a Data Scientist or ML Engineer, you will get a set of tools and practices to overcome some pain points, manage ML experiments and models in the right way and automate silos.
• As a Team Lead or Chief of Data, you definitely need to have a clear vision of the MLOps process. The talk accumulates personal experience and experience of different teams around the globe.

Speaker

Rozhkov Mikhail, Solutions Engineer, Iterative.ai
ML Engineer and enthusiast with over 7 years of experience in Machine Learning and Data Science. Co-creator ML REPA, author of courses on automating ML experiments with DVC and MLOps. As a member of the Iterative.ai team, he helps teams improve ML development and automate MLOps processes.

GitHub: https://github.com/mnrozhkov
LinkedIn: https://www.linkedin.com/in/mnrozhkov

Sponsorship

This meet-up of the DATA SCIENCE CLUB BELGRADE group is sponsored by DataKolektiv.